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continual learning setup
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commands/retrospective.md
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73
commands/retrospective.md
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description: Analyze the current session and extract learnings to memory
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allowed-tools: Read, Edit
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---
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# Session Retrospective
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Analyze this coding session and extract valuable learnings to improve future sessions.
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## Your Task
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### 1. Review What Happened This Session
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Reflect on the session:
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- What code was written or modified?
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- What problems were solved?
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- What approaches were tried (both successful and unsuccessful)?
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- Were there any surprises or unexpected behaviors?
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### 2. Identify Learnings
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Extract insights in these categories:
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**Patterns (what worked well)**:
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- Successful approaches that should be reused
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- Code patterns that solved problems effectively
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- Workflows that were efficient
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**Failures (what to avoid)**:
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- Approaches that didn't work
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- Bugs that were encountered and their root causes
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- Time wasted on wrong paths
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- Assumptions that turned out to be wrong
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**Edge Cases**:
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- Tricky scenarios discovered
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- Non-obvious behavior found
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- Boundary conditions that matter
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**Technology Insights**:
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- Framework/library-specific knowledge gained
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- API quirks discovered
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- Performance considerations learned
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### 3. Update learnings.md
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Edit `.claude/skills/codebase-agent/learnings.md` and add new entries under the appropriate sections.
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Use this format for each entry:
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```markdown
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### [Short Descriptive Title]
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- **Context**: When does this apply?
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- **Learning**: What is the insight?
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- **Example**: (optional) Code snippet or concrete example
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- **Session**: [Date or brief session description]
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```
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### 4. Quality Guidelines
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Be selective about what to add:
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- **Add** genuinely useful, project-specific insights
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- **Skip** general programming knowledge (things any developer would know)
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- **Skip** one-time fixes that won't recur
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- **Avoid** duplicating existing entries
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- **Merge** with existing entries if they're related
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## Output
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Summarize:
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1. How many learnings were added (and to which categories)
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2. Brief description of the most important insights
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3. Any patterns emerging across sessions
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